Power Analysis of Directly-connected FPGA Clusters

Kensuke Iizuka, Haruna Takagi, Aika Kamei, Kazuei Hironaka, Hideharu Amano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Although low power consumption is a significant advantage of FPGA clusters, almost no power analyses with real systems have been reported. This study reports the detailed power consumption analyses of two FPGA clusters, namely, M-KUBOS and FiC, with power measurement tools and real applications. In both clusters, the type of logic design shells determines the base power consumption. For building clusters, the power for node communication links is mainly determined by the number of activated links and not influenced by the number of actually used links. Therefore, applying the link aggregation technique does not affect the power consumption. Increasing the clock frequency of the application logic mildly increases the power consumption. The obtained results suggest that the best way to reduce the total power consumption of an FPGA cluster and improve its performance is to use the minimum number of links for the application, apply link aggregation, and aggressively increase the clock frequency.

Original languageEnglish
Title of host publication25th IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL Chips 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665419895
DOIs
Publication statusPublished - 2022
Event25th IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL Chips 2022 - Tokyo, Japan
Duration: 2022 Apr 202022 Apr 22

Publication series

Name25th IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL Chips 2022 - Proceedings

Conference

Conference25th IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL Chips 2022
Country/TerritoryJapan
CityTokyo
Period22/4/2022/4/22

ASJC Scopus subject areas

  • Hardware and Architecture
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computer Networks and Communications

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